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Call for Papers
1st International Workshop on
Hybrid Artificial Intelligence and Enterprise Modelling
(HybridAIMS'23)
June 12-13, 2023, Zaragoza, SPAIN
https://hybridaims.com/
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IMPORTANT DATES:
- Paper submission: March 19th, 2023
- Notification of acceptance: April 4th, 2023
- Camera Ready: May 4th, 2023
Hybrid Artificial Intelligence is the research direction that
focuses on the
combination of two prominent fields sub-symbolic AI (e.g., machine
learning,
deep learning, neural networks) and symbolic AI (e.g., knowledge
graphs, knowledge
representation and reasoning, knowledge engineering,
knowledge-based systems).
Approaches from both fields have complementary strengths and
enable the creation of
Intelligent Information Systems (IIS). For example, whilst neural
networks can recognize
patterns in large amount of data, knowledge-based systems contain
domain knowledge and
enable logical reasoning and explainability of conclusions. AI
approaches are typically
integrated with application systems, which provide data for the AI
approaches and use
the results of these approaches for further processing. Thus, the
creation of IIS
requires high expertise in both AI approaches, knowledge about the
application domain
and IT knowledge. An early inclusion of domain experts in the
engineering process is
beneficial as it promotes a high quality of an IIS and would
reduce its building time.
Such an early inclusion is, however, challenging because
stakeholders from business and
IT have complementary skills and speak different languages: one
more technical and one more
business oriented. Enterprise Modelling (EM) can tackle this
challenge as it supports business
and IT alignment. It is an established approach for the conceptual
representation, design,
implementation, and analysis of information systems. This is of
relevance for AI approaches.
Graphical notation of enterprise models fosters human
interpretability, hence supporting
communication and decision-making, involving stakeholders from the
application domain, IT and AI.
The convergence of Hybrid Artificial Intelligence and Enterprise
Modelling promises to deliver
high value in the creation of Intelligent Information Systems.
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SUBMISSION GUIDELINES
In this workshop, we welcome full research papers (12 pages) and
short (position) papers (6 pages).
The accepted papers will be presented in time slots of 20 minutes
for regular papers and 15 minutes for short papers.
The quality of this workshop will be ensured by having each
contribution reviewed by at least three experts in the field.
The papers will be published in proceedings in Springer LNBIP
series and, thus, will be indexed.
To submit your paper you must use the EasyChair site of the CAiSE
2023 conference through the track
"Hybrid Artificial Intelligence and Enterprise Modelling for
Intelligent Information Systems (HybridAIMS23)".
Submissions must conform to Springer, LNCS format.
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LIST OF TOPICS
Possible topics include, but are not limited to:
Neuro-Symbolic Artificial Intelligence and Enterprise or Visual
Models
Hybrid Artificial Intelligence and Enterprise or Visual Models for
Human-in-the-Loop
Hybrid Artificial Intelligence in and for Enterprise Architecture
Hybrid Artificial Intelligence for Business Process Management
Hybrid AI and Visual Models for Ontology Learning
Hybrid Recommender Systems with Visual Models
Machine Learning, Deep Learning, Neural Networks, and Visual
Models for Human-in-the-Loop
Machine Learning for Knowledge Graphs or Ontology-based Models
Machine Learning in Ontology-based Case-Based Reasoning
Explainable AI through Enterprise Models
Low code approaches for, e.g., Knowledge Graphs, Machine Learning,
Knowledge Engineering, Hybrid AI Engineering
Visual Conceptual Models for, e.g., Ontology Constraints,
Knowledge Graph Embeddings, Machine Learning, Knowledge
Engineering
Domain-Specific Models for Domain Ontology or for Enterprise
Ontology
Knowledge Engineering, Representation and Reasoning and Visual
Conceptual Models
Ontologies and Visual Models for Rule-Based or Case-Based
Reasoning approaches
Semantic Technologies for actionable Enterprise Models
Combining Ontology-based Business Processes and Data-Driven
Approaches
Enterprise AI
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HybridAIMS 2023 ORGANIZING COMMITTEE
Co-Chairs:
Emanuele Laurenzi
Hans Friedrich Witschel
Peter Haase
Contact:
info@hybridaims.com<mailto:info@hybridaims.com>
_______________________________________________________________________________
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FHNW - University of Applied Sciences and Arts Northwestern
Switzerland
School of Business
Dr. Emanuele
Laurenzi
<https://www.fhnw.ch/en/people/emanuele-laurenzi>,
Lecturer and Senior Researcher in Intelligent Information Systems
& Innovation
PhD in Information Systems
Riggenbachstrasse 16<x-apple-data-detectors://2/> (room ORI
209)
4600 Olten, Switzerland<x-apple-data-detectors://2/>
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T +41 76 789 33 16
P +41 62 957 28 26
emanuele.laurenzi@fhnw.ch<mailto:emanuele.laurenzi@fhnw.ch>
https://www.fhnw.ch/en/people/emanuele-laurenzi
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